Comparison of Three Atherosclerotic Cardiovascular Disease Risk Scores With and Without Coronary Calcium for Predicting Revascularization and Major Adverse Coronary Events in Symptomatic Patients Undergoing Positron Emission Tomography-Stress Testing

A highly predictive cardiac positron emission tomography (PET) risk score for 90-day and one-year major adverse cardiac events and revascularization

BACKGROUND

With the increase in cardiac PET/CT availability and utilization, the development of a PET/CT-based major adverse cardiovascular events, including death, myocardial infarction (MI), and revascularization (MACE-Revasc) risk assessment score is needed. Here we develop a highly predictive PET/CT-based risk score for 90-day and one-year MACE-Revasc.

METHODS AND RESULTS

11,552 patients had a PET/CT from 2015 to 2017 and were studied for the training and development set. PET/CT from 2018 was used to validate the derived scores (n = 5049). Patients were on average 65 years old, half were male, and a quarter had a prior MI or revascularization. Baseline characteristics and PET/CT results were used to derive the MACE-Revasc risk models, resulting in models with 5 and 8 weighted factors. The PET/CT 90-day MACE-Revasc risk score trended toward outperforming ischemic burden alone [P = .07 with an area under the curve (AUC) 0.85 vs 0.83]. The PET/CT one-year MACE-Revasc score was better than the use of ischemic burden alone (P < .0001, AUC 0.80 vs 0.76). Both PET/CT MACE-Revasc risk scores outperformed risk prediction by cardiologists.

CONCLUSION

The derived PET/CT 90-day and one-year MACE-Revasc risk scores were highly predictive and outperformed ischemic burden and cardiologist assessment. These scores are easy to calculate, lending to straightforward clinical implementation and should be further tested for clinical usefulness.

Comparing the pooled cohort equations and coronary artery calcium scores in a symptomatic mixed Asian cohort

Background

The value of pooled cohort equations (PCE) as a predictor of major adverse cardiovascular events (MACE) is poorly established among symptomatic patients. Coronary artery calcium (CAC) assessment further improves risk prediction, but non-Western studies are lacking. This study aims to compare PCE and CAC scores within a symptomatic mixed Asian cohort, and to evaluate the incremental value of CAC in predicting MACE, as well as in subgroups based on statin use.

Methods

Consecutive patients with stable chest pain who underwent cardiac computed tomography were recruited. Logistic regression was performed to determine the association between risk factors and MACE. Cohort and statin-use subgroup comparisons were done for PCE against Agatston score in predicting MACE.

Results

Of 501 patients included, mean (SD) age was 53.7 (10.8) years, mean follow-up period was 4.64 (0.66) years, 43.5% were female, 48.3% used statins, and 50.0% had no CAC. MI occurred in 8 subjects while 9 subjects underwent revascularization. In the general cohort, age, presence of CAC, and ln(Volume) (OR = 1.05, 7.95, and 1.44, respectively) as well as age and PCE score for the CAC = 0 subgroup (OR = 1.16 and 2.24, respectively), were significantly associated with MACE. None of the risk factors were significantly associated with MACE in the CAC > 0 subgroup. Overall, the PCE, Agatston, and their combination obtained an area under the receiver operating characteristic curve (AUC) of 0.501, 0.662, and 0.661, respectively. Separately, the AUC of PCE, Agatston, and their combination for statin non-users were 0.679, 0.753, and 0.734, while that for statin-users were 0.585, 0.615, and 0.631, respectively. Only the performance of PCE alone was statistically significant (p = 0.025) when compared between statin-users (0.507) and non-users (0.783).

Conclusion

In a symptomatic mixed Asian cohort, age, presence of CAC, and ln(Volume) were independently associated with MACE for the overall subgroup, age and PCE score for the CAC = 0 subgroup, and no risk factor for the CAC > 0 subgroup. Whilst the PCE performance deteriorated in statin versus non-statin users, the Agatston score performed consistently in both groups.

Machine learning derived ECG risk score improves cardiovascular risk assessment in conjunction with coronary artery calcium scoring

Background

Precision estimation of cardiovascular risk remains the cornerstone of atherosclerotic cardiovascular disease (ASCVD) prevention. While coronary artery calcium (CAC) scoring is the best available non-invasive quantitative modality to evaluate risk of ASCVD, it excludes risk related to prior myocardial infarction, cardiomyopathy, and arrhythmia which are implicated in ASCVD. The high-dimensional and inter-correlated nature of ECG data makes it a good candidate for analysis using machine learning techniques and may provide additional prognostic information not captured by CAC. In this study, we aimed to develop a quantitative ECG risk score (eRiS) to predict major adverse cardiovascular events (MACE) alone, or when added to CAC. Further, we aimed to construct and validate a novel nomogram incorporating ECG, CAC and clinical factors for ASCVD.

Methods

We analyzed 5,864 patients with at least 1 cardiovascular risk factor who underwent CAC scoring and a standard ECG as part of the CLARIFY study (ClinicalTrials.gov Identifier: NCT04075162). Events were defined as myocardial infarction, coronary revascularization, stroke or death. A total of 649 ECG features, consisting of measurements such as amplitude and interval measurements from all deflections in the ECG waveform (53 per lead and 13 overall) were automatically extracted using a clinical software (GE Muse™ Cardiology Information System, GE Healthcare). The data was split into 4 training (S_tr) and internal validation (S_v) sets [S_tr (1): S_v (1): 50:50; S_tr (2): S_v (2): 60:40; S_tr (3): S_v (3): 70:30; S_tr (4): S_v (4): 80:20], and the results were compared across all the subsets. We used the ECG features derived from S_tr to develop eRiS. A least absolute shrinkage and selection operator-Cox (LASSO-Cox) regularization model was used for data dimension reduction, feature selection, and eRiS construction. A Cox-proportional hazards model was used to assess the benefit of using an eRiS alone (M_ecg), CAC alone (M_cac) and a combination of eRiS and CAC (M_ecg+cac) for MACE prediction. A nomogram (M_nom) was further constructed by integrating eRiS with CAC and demographics (age and sex). The primary endpoint of the study was the assessment of the performance of M_ecg, M_cac, M_ecg+cac and M_nom in predicting CV disease-free survival in ASCVD.

Findings

Over a median follow-up of 14 months, 494 patients had MACE. The feature selection strategy preserved only about 18% of the features that were consistent across the various strata (S_tr). The M_ecg model, comprising of eRiS alone was found to be significantly associated with MACE and had good discrimination of MACE (C-Index: 0.7, p = <2e-16). eRiS could predict time-to MACE (C-Index: 0.6, p = <2e-16 across all S_v). The M_ecg+cac model was associated with MACE (C-index: 0.71). Model comparison showed that M_ecg+cac was superior to M_ecg (p = 1.8e-10) or M_cac (p < 2.2e-16) alone. The M_nom, comprising of eRiS, CAC, age and sex was associated with MACE (C-index 0.71). eRiS had the most significant contribution, followed by CAC score and other clinical variables. Further, M_nom was able to identify unique patient risk-groups based on eRiS, CAC and clinical variables.

Conclusion

The use of ECG features in conjunction with CAC may allow for improved prognostication and identification of populations at risk. Future directions will involve prospective validation of the risk score and the nomogram across diverse populations with a heterogeneity of treatment effects.

Assessment of Cardiovascular Disease Risk: A 2022 Update

Assessment of atherosclerotic cardiovascular disease (ASCVD) risk is the cornerstone of primary ASCVD prevention, enabling targeted use of the most aggressive therapies in those most likely to benefit, while guiding a conservative approach in those who are low risk. ASCVD risk assessment begins with the use of a traditional 10-year risk calculator, with further refinement through the consideration of risk-enhancing factors (particularly lipoprotein(a)) and subclinical atherosclerosis testing (particularly coronary artery calcium (CAC) testing). In this review, we summarize the current field of ASCVD risk assessment in primary prevention and highlight new guidelines from the Endocrine Society.

Spectrum of radionuclide perfusion study abnormalities in takotsubo cardiomyopathy

BACKGROUND

Takotsubo (stress) cardiomyopathy (TCM) is characterized by transient apical left ventricular dysfunction precipitated by emotional or physical stress. Its presentation makes it difficult to differentiate from an acute coronary syndrome. A suggestive echocardiogram plus normal coronary angiography most often are used for diagnosis. Radionuclide perfusion study (RPS) findings in TCM, including by positron emission tomography (PET), have been poorly characterized.

METHODS AND RESULTS

Intermountain Healthcare electronic medical records were searched from 2009 to 2019 for patients with a discharge diagnosis of TCM, stress CM, or takotsubo syndrome. 16 TCM patients with an RPS, including by PET in 8, were identified: 13 (81%) were women; age averaged 72 years (50-89 years); 14 had an identified stressor. TCM diagnosis was definite in 11 and probable/possible in 5. RPS was abnormal in 11, with 9 showing an apical perfusion deficit, whereas angiography in 14 showed normal coronaries in 12 and non-obstructive disease in 2. Echo ejection fraction averaged 41% (29%-60%); an apical wall motion abnormality was present in 14 (88%). Troponin elevations were noted in 14/15. The presenting ECG was abnormal is 14, frequently showing ST-T-wave abnormalities. 13 patients were discharged on a beta-blocker. Follow-up echo (in 12) showed recovered ejection fraction in 9 and recovered apical wall motion in 11.

CONCLUSIONS

Despite having normal or non-obstructive epicardial coronary arteries on angiography, TCM patients frequently present with apical wall motion abnormalities and matching RPS perfusion defects. These findings suggest microvascular abnormalities, whose pathophysiology, temporal course, and clinical implications should be the subject of further investigation.

Absent or Mild Coronary Calcium Predicts Low-Risk Stress Test Results and Outcomes in Patients Considered for Flecainide Therapy

BACKGROUND

Flecainide is a useful antiarrhythmic for atrial fibrillation (AF). However, because of ventricular proarrhythmia risk, a history of myocardial infarction (MI) or coronary artery disease (CAD) is a flecainide exclusion, and stress testing is used to exclude ischemia. We assessed whether absent/mild coronary artery calcium (CAC) can supplement or avoid the need for stress testing.

METHODS

We assessed ischemic burden using regadenoson Rb-82 PET/CT in 1372 AF patients ≥50 years old without symptoms or signs of clinical CAD. CAC was determined qualitatively by low dose attenuation computed tomography (CT) (n = 816) or by quantitative CT (n = 556). Ischemic burden and clinical outcomes were compared by CAC burden.

RESULTS

Patients with CAC absent or mild (n = 766, 57.2%) were younger, more frequently female, and had higher BMI but lower rates of diabetes, hypertension, and dyslipidemia. Average ischemic burden was lower in CAC-absent/mild patients, and CAC-absent/mild patients showed greater coronary flow reserve, had fewer referrals for coronary angiography, and less often had obstructive CAD. Revascularization at 90 days was lower, and the rate of longer-term major adverse cardiovascular events was favorable.

CONCLUSIONS

An easily administered, inexpensive, low radiation CAC scan can identify a subset of flecainide candidates with a low ischemic burden on PET stress testing that rarely needs coronary angiography/intervention and has favorable outcomes. Absent or mild CAC-burden combined with other clinical information may avoid or complement routine stress testing. However, additional, ideally randomized and multicenter trials are indicated to confirm these findings before replacing stress testing with CAC screening in selecting patients for flecainide therapy in clinical practice.